AnthropicAnnouncement
Claude Science, an AI workbench for scientists
Summary
Claude Science is a beta AI workbench for scientists that brings databases, research tools, computing resources, and domain-specific workflows into one environment. Researchers can analyze literature, run multi-step studies, create figures and manuscripts, and revise them through conversation. Every generated artifact includes its code, environment, plain-language creation description, and message history, while a reviewer agent checks citations, calculations, and consistency between figures and code. A coordinating agent uses more than 60 curated skills and connectors across fields including genomics, single-cell, proteomics, structural biology, and cheminformatics; it can manage jobs on local systems, HPC clusters over SSH, or Modal, scaling from one GPU to hundreds. Beta access is available on macOS and Linux for Pro, Max, Team, and Enterprise users, with reported examples including faster glioma analyses and large literature reviews.
Context
Scientific research requires working across many databases with different schemas, bespoke pipelines for file formats, and separate tools such as PubMed, Jupyter, R, and cluster terminals. Large analyses also require researchers to manage computing jobs and move results between systems.
Approach / What changed
Claude Science combines scientific tools, databases, packages, skills, connectors, agents, and computing resources in one research environment. It generates reproducible artifacts with code and execution context, manages jobs on local or HPC infrastructure and Modal, supports reusable lab skills, and uses reviewer agents to inspect citations, calculations, and outputs.
Takeaways
Generated figures and manuscripts include the exact code and environment used, a plain-language creation description, and the full message history, supporting later validation and reproduction.
Claude Science can ask before accessing new resources and submit jobs to an existing HPC cluster over SSH or to Modal, scaling analyses from a single GPU to hundreds.
A beta workflow at the Allen Institute produced about 10 long reviews with reviewer-checked citations, while one UCSF lab reported comprehensive germline analyses in roughly one-tenth of the previous time and independently validated the results.
Source and freshness
- Source
- anthropic.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
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